Philippines vs Tanzania

Philippines vs Tanzania: Tropical nights

Tropical nights in 2014: 331.5 nights in Philippines and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Philippines, by 225.2 nights, or 3.12 times that in Tanzania.

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nights a year · CMIP6

Philippines vs Tanzania: Tropical nightsTropical nights in 2014: 331.5 nights in Philippines and 106.3 nights in Tanzania, in the CMIP6 climate models’ median run. In 2014 the value was higher in Philippines, by 225.2 nights, or 3.12 times that in Tanzania.
PhilippinesTanzaniaCMIP6 model median (SSP2-4.5, middle of the road)models’ 10th–90th percentile

What the numbers say

  • Philippines has been higher in every year both have figures for since 1950.
  • The CMIP6 model median (SSP2-4.5, middle of the road) puts Philippines at 351.3 nights and Tanzania at 208 nights in 2100.

Every year

nights a year · CMIP6

YearPhilippinesTanzania
2014331.5106.3
2013330.9105.5
2012331.1108.4
2011329.8109
2010330.6103.9
2009329101.1
2008327.5100.3
2007327.899.5
2006328.7100.4
2005329.798.7
2004329.4100.4
2003327.199.6
2002328.998.4
2001327.8101.5
2000326.894.9
1999327.594.2
1998326.596.8
1997325.493.5
1996324.689.6
1995324.288.5
1994321.585.4
1993319.581.2
1992318.480.1
1991324.189.6
1990323.591.1
1989322.589.1
198832487.6
1987323.188.5
1986322.189.4
1985321.483
1984321.783.1
1983319.482.1
1982320.584.8
1981320.488
1980322.785
1979321.285.5
1978320.682.9
1977319.884.1
1976319.681
1975319.680.8
197432082.2
1973319.483.6
1972318.981.4
1971318.880.7
197031981.8
1969318.779.5
1968317.279.1
1967317.477.5
1966318.878.1
1965317.278
1964314.973.8
1963317.273.1
1962318.681.1
1961319.382.6
1960318.683.9
1959320.581.4
1958321.882.1
1957319.480.9
195632080
1955319.381.6
1954317.781.4
195332080.6
195231981.4
1951319.882.1
1950320.480.7
CMIP6 model median (SSP2-4.5, middle of the road) · 2015–2100
YearPhilippinesTanzania
2015333319.8–339.5114.895.2–137.4
2016334.2322.8–340.7108.391.6–125.6
2017333.4319.7–339.8114.893.6–137.8
2018333.2320.1–340.1116.497.4–137.1
2019334.1323.4–341.2113.495.2–133.2
2020334.6322.6–341.8119.396.2–143.5
2021335.6323.3–341.1119.5100.9–147.1
2022335.7323.3–342.1124.4105.3–147.4
2023336.7324.8–343.2122.1102.1–147.8
2024337.2325.7–343.9126.2100–150.1
2025336.3326.2–342.8124.6100.9–154
2026336.5322.9–343126.999.1–155.6
2027336.2325.7–342.3128102.9–147.7
2028337.1325.5–343.8129.9106.4–152.1
2029338.1327.2–344.6134.1111–156.5
2030337.7326.2–344.4129.4106.4–151.1
2031337.1325.6–343.8136.4115.9–158.4
2032339.4329.5–346.1135.1114–166.8
2033339.7329.6–345.5135.2110.9–161.9
2034338.8328.8–345134.7112.5–166.3
2035338.6327.5–346.4140.2114.6–165
2036339.6327.8–346.9137.8113.3–165.5
2037339.8329.1–345.5142.9121.5–168.9
2038341.9330.7–347.7147.9124.3–169.3
2039341.2330.4–346.9144.3117.6–171.3
2040340.4328.1–347.6140.5117–178
2041341.1329.1–346.7149.1121.7–175.6
2042342331.4–347.7146.3120.5–185.3
2043341.3329–348.1144.6117–173
2044342.8329.9–349.8147.7121.2–175.8
2045343.4333.8–348.7150.1125.2–183.4
2046342.7330.2–348.7161.5128.6–192.2
2047343.2331.7–350.6160.2129.7–194.4
2048343.3332.7–350.6158.8132.7–193.1
2049343.2332.5–349.5157.6131.1–196
2050344.3332.6–349.9159.7127.8–192
2051344.4334.9–350.8163.2135.5–197.8
2052344.1333.5–350.9161.9136.2–199.1
2053344.3333.6–350.3160.6127.5–197.7
2054343.4332–349.9163.2131.5–200.2
2055344.3334.4–350.5167.4137–208.3
2056345334.6–352.6166.4130.8–209.7
2057345.5335.1–351.5168134.6–208.3
2058345.8334.3–351.3168.7134.9–210.3
2059345.5333.7–351.6174.7144.9–219.5
2060346.8335.5–353.5181.7138.1–219.8
2061345.9335–351.8171.8135.5–218.1
2062346335.2–353.5177.5139.9–224
2063346.6336.2–352.8181.4140.1–213.8
2064346.9335.3–353185.3140.1–215.2
2065346.1335.9–351.9183.5141.1–221.8
2066346.5335.4–352.4181.9146.3–219.3
2067346.1335.4–352178.8138.8–229.2
2068347.1335.1–354.1186144.2–228.4
2069347333.8–353.6183.7141.7–225.3
2070346.7336.1–352.7180.7140.4–228.2
2071347.6336.2–353.9184.9146.9–235.2
2072347334.4–353.8191.3155–226.1
2073348.4336.7–355191.6152.4–235.6
2074348.6337–354.9183.3149.7–231.7
2075347.9337.2–354183.8144.8–233
2076348.4337–355.1191.1150.9–233.2
2077348.7337–354.8191.3152.6–238.2
2078348.4338.2–354.7189156.6–233.8
2079348.8337.6–354.7190.5147–237.3
2080349.1338.4–355.9197.3150.7–241.2
2081348.8336.9–355.1195.6153.4–237.4
2082349.6338–354.9194.5157.3–237.3
2083349.9337.9–356.1193.2151–249.8
2084349.5336.7–356.4201.1152.2–246.7
2085349.1338.2–355.4204.2162.3–252.3
2086349.4337.5–354.9195156–248.7
2087349.7338.7–356196.7160.8–244.5
2088349.9338.9–356.1208.4154.7–246.9
2089350.2339.8–355.2201.3158.6–248.2
2090350.1339.7–355.9197.9160.7–253.6
2091349.5339.5–356.3210161.6–256
2092350.5339.3–356.1205.8158.3–253.6
2093350.4337.9–356.5207.2161.2–251.9
2094350.5338.4–355.9207.9161.3–250.6
2095350.5338.3–355.7214.2166.4–258.5
2096351.1339–358205.3159.8–257.4
2097350.2339.3–355.6206.6158.4–256.8
2098350.3337.4–355.2209.1161–258.3
2099350.6339.3–356.4208.5160.1–256
2100351.3340.2–356.3208158.6–258.6

Each country on its own

Good to know

  • Nights in a year when the temperature stays above 20 °C, averaged over the country.
  • Source: World Bank Climate Change Knowledge Portal, CMIP6 multi-model median.
  • The dashed line is the CMIP6 model median (SSP2-4.5, middle of the road), a scenario rather than a forecast; the band is its models’ 10th–90th percentile.
  • Climate model values are the median of the CMIP6 models, run on past emissions to 2014 and on SSP2-4.5, a middle-of-the-road path, after: they are not measurements.

How the layers work, where their data comes from and what they can’t tell you: Countries through time

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